Abstract
Phaseolus vulgaris L. is the most commonly consumed legume in the world, given its high vegetable protein content, phenolic compounds, and antioxidant properties. It also represents one of the most sustainable, low-carbon and sources of food available at present to man. This study aims to identify the nutrients, antinutrients, phenolic composition, and antioxidant profile of 10 common bean cultivars (Arikara yellow, butter, cranberry, red kidney, navy, pinto, black, brown eyed, pink eyed, and tarrestre) from two harvest years, thereby assessing the potential of each cultivar for specific applications in the food industry. Navy and pink eyed beans showed higher potential for enrichment of foodstuffs and gluten-free products due to their higher protein and amino acid contents. Additionally, red kidney, cranberry and Arikara yellow beans had the highest content of phenolic compounds and antioxidant properties, which can act as functional ingredients in food products, thus bringing health benefits. Our study highlights the potential of using specific bean cultivars in the development of nutrient-enriched food and as functional ingredients in diets designed for disease prevention and treatment.

Abstract
Genetic improvement in grapevine (Vitis vinifera L.) is performed mainly through clonal selection processes. This procedure takes advantage of the intro-varietal genetic variability existing in ancient varieties. It focuses on the selection of the most promising genotypes for certain quantitative characteristics, such as yield, soluble solids content, acidity, anthocyanins, tannins, among others, always preserving the intra-varietal diversity. In the present work, we evaluated the performance of 30 clones of Tempranillo' grape in two distinct trial sites at the Douro Demarcated Region (DDR), Cavernelho and Sao Luiz, during two consecutive years, measuring phytochemical content and oenological potential parameters. Significant differences between clones related to phytochemical content and antiradical activity, were observed in the Cavernelho and Sao Luiz fields, besides some oenological parameters in Sao Luiz. Among years, significant differences for clones, in total phenols and antiradical activity by the DPPH method were observed in both fields. In Sao Luiz, such differences were also found for the contents in anthocyanins, flavonoids and ortho-diphenols. Concerning the differences between samples from the same clone in the two fields, the greatest number of significant differences was observed for the anthocyanins content in 2016. A set of ten Tempranillo' grape clones displayed behavioral stability associated with appropriate values of soluble solids, titratable acidity and phytochemical content.

Abstract
Common beans (Phaseolus vulgaris L.), represent the most consumed legume worldwide and constitute an important source of protein, being also known to contain antinutritional compounds, which compromise nutrients' bioavailability. However, the standard methodologies to assess these constituents are time-consuming and complex. Therefore, the present study evaluated the suitability of near-infrared (NIR) and mid-infrared (MIR) spectroscopies for the development of simple and reliable methods to assess protein, lipids, tannins and phytic acid contents, besides specific amino acids, in whole bean flours. Partial least squares (PLS) regression was used to develop analytical models, and external validation was performed. NIR displayed better performance for the evaluation of protein, lipids, tannins and phytic acid contents, and MIR, for the assessment of specific amino acids. In both techniques, the use of the 1st derivative was the best data treatment. Overall, both techniques represent reliable methods to evaluate the proximate and antinutritional composition of bean flours.

Abstract
A series of metal-organic coordination complexes based on alkaline-earth metal centers [Mg(II), Ca(II), and Ba(II)] and the ligand 5-aminoisophthalate (aip(2-)) revealed notable structural diversity, both in the materials' dimensionality and in their hydrogen bonding networks: [Mg(H2O)(6)].[Mg-2(Haip)(H2O)(10)].(Haip).3(aip).10(H2O) (1) and [Mg(aip)(phen)(H2O)(2)].(H2O) (2) were isolated as discrete complexes (0D); [Ca(aip)(H2O)(2)].(H2O) (3), [Ca(aip)(phen)(H2O)(2)].(phen).(H2O) (4), and [Ba-2(aip)(2)(phen)(2)(H2O)(7)].2(phen).2(H2O) (5) revealed metal-organic chain (1D) structures, while the [Ba(aip)(H2O)] (6) showed a metal-organic layered (2D) arrangement. Furthermore, most of these metal-organic coordination materials revealed interesting thermal stability properties, being stable at temperatures up to 450 degrees C.

Abstract
Developing ground robots for crop monitoring and harvesting in steep slope vineyards is a complex challenge due to two main reasons: harsh condition of the terrain and unstable localization accuracy obtained with Global Navigation Satellite System (GNSS). In this context, a reliable localization system requires an accurate detector for high density of natural/artificial features. In previous works, we presented a novel visual detector for Vineyards Trunks and Masts (ViTruDe) with high levels of detection accuracy. However, its implementation on the most common processing units -central processing units (CPU), using a standard programming language (C/C++), is unable to reach the processing efficiency requirements for real time operation. In this work, we explored parallelization capabilities of processing units, such as graphics processing units (GPU), in order to accelerate the processing time of ViTruDe. This work gives a general perspective on how to parallelize a generic problem in a GPU based solution, while exploring its efficiency when applied to the problem at hands. The ViTruDe detector for GPU was developed considering the constraints of a cost-effective robot to carry-out crop monitoring tasks in steep slope vineyard environments. We compared the proposed ViTruDe implementation on GPU using Compute Unified Compute Unified Device Architecture(CUDA) and CPU, and the achieved solution is over eighty times faster than its CPU counterpart. The training and test data are made public for future research work. This approach is a contribution for an accurate and reliable localization system that is GNSS-free.

Abstract
Integrate-and-fire (IFN) model of a biological neuron is an amplitude-to-time conversion technique that encodes information in the time-spacing between action potentials (spikes). In principle, this encoding scheme can be used to modulate signals in an impulse radio ultra wide-band (IR-UWB) transmitter, making it suitable for low-power applications, such as in wireless sensor networks (WSN) and biomedical monitoring. This paper then proposes an architecture based on IFN encoding method applied to a UWB transceiver scenario, referred to herein as impulse-radio integrate-and-fire (IRIF) transceiver, followed by a system-level study to attest its effectiveness. The transmitter is composed of an integrate-and-fire modulator, a digital controller and memory block, followed by a UWB pulse generator and filter. At the receiver side, a low-noise amplifier, a squarer, a low-pass filter and a comparator form an energy-detection receiver. A processor reconstructs the original signal at the receiver, and the quality of the synthesized signal is then verified in terms of effective number of bits (ENOB). Finally, a link budget is performed. (C) 2019 Published by Elsevier GmbH.